> Markdown version of [/jobs/ext/2297279-software-engineer](https://www.wearedevelopers.com/jobs/ext/2297279-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Aleph America Corporation - **Location:** Latin America, United States (Remote available) - **Experience:** Expert - **Salary:** $130,000.0 - $350,000.0 - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Large Language Models, Multi-Agent Systems - **Published:** August 29, 2026 - **Apply:** https://www.workingnomads.com/job/go/1818847/ ## About the Role * You've shipped production LLM systems - evals, context management, multi-model or multi-provider routing - and can talk concretely about what broke and what you changed * You build proof of concepts, decide quickly, and ship v0s. Evals drive your quality bar * Strong judgment about abstractions: opinionated about design, pragmatic about shipping incrementally * Experience with LLM APIs and agent frameworks, and shipped user-facing products * You want to ship production systems, not do research ## Description * Own the AI foundation product teams build on: model selection and routing, the model proxy layer, context management, and tool design * Own eval infrastructure. Work with customers and finance domain experts to define what excellent output looks like, then encode it in evals every team can run - in FP&A, a wrong answer ends up in someone's board deck * Ship agentic features end to end, from v0 through the optimization loop: prompt and context engineering, caching, parallel tool calls, subagent patterns * Build observability into agent behavior so we can profile it, find bottlenecks, and decide what to fix with data * Track what's changing in agentic systems and bring the practices that prove out into how we build ## Related Videos - [Designing and Deploying Distributed Multimodal Multi-Agent Systems with Google's AI Stac](https://www.wearedevelopers.com/videos/1976-designing-and-deploying-distributed-multimodal-multi-agent-systems-with-google-s-ai-stac) - [Creating Industry ready solutions with LLM Models](https://www.wearedevelopers.com/videos/899-creating-industry-ready-solutions-with-llm-models) - [Edit Your Future: Queerverse Radical AI](https://www.wearedevelopers.com/videos/909-edit-your-future-queerverse-radical-ai) - [LLMs in the wild: Building an AI agent that survives production](https://www.wearedevelopers.com/videos/100319-llms-in-the-wild-building-an-ai-agent-that-survives-production) - [Bringing the power of AI to your application.](https://www.wearedevelopers.com/videos/1010-bringing-the-power-of-ai-to-your-application) - [Building Scalable Multi-Agentic AI Systems in Java: Orchestrating Agents with Event-Driven Approach](https://www.wearedevelopers.com/videos/1967-building-scalable-multi-agentic-ai-systems-in-java-orchestrating-agents-with-event-driven-approach) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [Never delegate the understanding](https://www.wearedevelopers.com/magazine/749-never-delegate-the-understanding) - [How We Built a Worry-Free System That Runs for 10+ Years – And What We’d Do Again](https://www.wearedevelopers.com/magazine/751-how-we-built-a-worry-free-system-that-runs-for-10-years-and-what-we-d-do-again) - [From Prototype to Production: Build AI Agents with This Free 4-Course Learning Path](https://www.wearedevelopers.com/magazine/655-from-prototype-to-production-build-ai-agents-with-this-free-4-course-learning-path) - [A 5-Step Open-Source Setup for Agentic Engineering](https://www.wearedevelopers.com/magazine/738-a-5-step-open-source-setup-for-agentic-engineering) - [Dev Digest 121 - AI goes offline](https://www.wearedevelopers.com/magazine/456-dev-digest-121-ai-goes-offline)